Household food insecurity is associated with both body mass index and middle upper-arm circumference of mothers in northwest Ethiopia: A comparative study

Background: Food insecurity and associated malnutrition result in serious health problems in developing countries. This study determined levels of maternal undernutrition and its association with food insecurity in northwest Ethiopia. Materials and methods: This was a community-based comparative cross-sectional study conducted May 24–July 20, 2013. Multistage random sampling was used to select 4,110 samples. Availability of Ethiopia’s Productive Safety Net Programme was used for grouping the study areas. A food-security access scale developed by the Food and Nutrition Technical Assistant project was used to measure food security. Sociodemographic data were collected using a structured questionnaire. A binary logistic regression model was used to assess the association of food insecurity and maternal undernutrition. Results: From the total participants, 12.6% (95% confidence interval [CI] 11.6%–13.6%) had a body mass index (BMI) <18.5 kg/m2. Comparison of maternal undernutrition in the two study areas revealed 8.8% (95% CI 7.6%–10.2%) in the program area and 16.4% (95% CI 14.8%–18.1%) in nonprogram areas were undernourished. Severe food insecurity was significantly associated with BMI of mothers (adjusted odds ratios [AORs] 3.6 and 2.31, 95% CI 2.32–5.57 and 1.52–3.5, respectively) in both program and nonprogram areas. Mild (AOR 1.77, 95% CI 1.21–2.6) and moderate (AOR 1.6, 95% CI 1.18–2.16) food insecurity significantly associated with maternal undernutrition in nonprogram areas. In the same way, all forms of food insecurity significantly associated with maternal middle upper-arm circumference in both program and nonprogram areas. The odds of mothers who did not exercise decision-making practice on the household income was also 4.13 times higher than those who did (AOR 4.13, 95% CI 2.2–7.77) in the program area. Conclusion: Food insecurity significantly associated with both maternal BMI and middle upper-arm circumference in both study areas. Female authority also significantly associated with BMI of the mothers in the program area. Maternal nutrition-intervention programs should focus on women-empowerment strategies that enable them to decide on the income for household-nutrition provision.

The study was conducted in Amhara regional state, which covers some 157,647 km2 across northwestern and eastern Ethiopia and has a total projected population of 20,018,999 (10,011,795 males and 10,007,204 females), based on the 2007 census.18,19 The region is divided into a number of highland blocks separated by deep river valleys and the eastern and western escarpments and their associated lowlands.19 Specifically, the study was conducted in the East and West Gojjam zones of the region. East Gojjam has a total population of 2,451,959 (1,199,952 males and 1,252,006 females). West Gojjam has a total population of 2,474,254 (1,220,477 males and 1,253,777 females).18 The mean annual temperatures of the region are 22°C–27°C in the lowlands and 10°C–22°C in the highlands up to 3,000 m above sea level.19 Within the region, four major cereal systems have been recognized: the sorghum–maize system in the lowland agroecological zone, the wheat–teff system in the single-rain-season area of the midland agroecological zone, the wheat–teff system in the double rain seasons of the midland agroecological zone, and the barley system in the highland agroecological zone.19 The study considered two zones classified by their agricultural production: one with the Productive Safety Net Programme and one without the program. A community-based comparative cross-sectional study design was used to determine the level of maternal under-nutrition and the association between food insecurity and undernutrition. The comparison was used for food-security determination in the two study areas. Households in the study areas were used as a sampling unit, and all necessary data were drawn from the mothers. The two groups were considered based on the availability of the Productive Safety Net Programme: group 1 with the program and group 2 without the program. The current study used the sample size determined for another larger study that was used to determine nutritional status of children aged under 5 years and the association between food insecurity and child under-nutrition (the detail is available elsewhere).20 The required sample size for the other study was 4,110 households, and the adequacy of the sample size for the current study to address both levels of maternal nutritional status and the association between food insecurity and maternal undernutrition was checked and found to be sufficient. With similar assumptions and presence of food insecurity as an exposure and maternal undernutrition (33% for program area and 27% for nonprogram area) as an outcome variable, the estimated sample size was 3,017 households, which is less than the current sample. Therefore, a sample of 4,110 was considered sufficient for the analysis. Multistage random sampling technique was employed to reach and select the final study units. In the first place, the two zones (East and West Gojjam) were selected purposely by taking into account the variability and absence of the Productive Safety Net Programme in the two zones. East Gojjam was selected as it has the program, while West Gojjam is considered a nonprogram area. Six districts from the two zones (three from each zone) were selected. All three districts in East Gojjam covered by the program (Enebsie Sar Midir, Goncha Siso Enese, and Shebel Berenta) were selected and included in the study. Three districts in West Gojjam (Mecha, North Achefer, and Jabi Tehinan) were selected randomly from the total 14 districts. The two zones are more comparable on many sociocultural characteristics than the other zones of the region. Once the six districts (three from each zone) had been identified, kebeles (the smallest administrative unit in the country) were randomly selected from these selected districts. The kebeles were selected based on agroecological zones and urban/rural settings. Four town kebeles (two from each zone), three rural highland kebeles (two from the nonprogram area, and one from the program area; it was proposed to include two highland kebeles from the program area, but unfortunately there was only one highland kebele covered by the program). The other eleven rural midland kebeles (six from the program area and five from the nonprogram area) and six rural lowland kebeles (three from each area) were selected randomly. Then, the total sample size was distributed to the kebeles proportionally. The households from these kebeles were selected using systematic random sampling using household registration as a sampling frame. For the program area, program registration was used as a sampling frame. The total number of households in each kebele was divided by the allocated sample size to get the sampling interval. The first household was identified by lottery, and then the spin of a bottle. When there were no children aged under 5 years in the identified household, the next household was used as a sampling unit. This was done because the data-collection process included children aged under 5 years. When there was more than one mother with children aged under 5 years in the same household, one mother was selected by lottery. A structured questionnaire adapted from different standard questionnaires15,21 and anthropometric measuring devices were used to collect the data. Some of the areas in the questionnaire included sociodemographic characteristics, such as household head, marital status, family size, educational level, occupation, female authority, household monthly income, household food security/insecurity, and food/dietary diversity. Female-authority information was collected by asking the respondent mothers whether they had the right to exercise decision-making practices on the household income. Specifically, respondents asked whether they sold income-generating items and bought food supplies for household consumption by themselves or not. Two alternative answers (0 for no and 1 for yes) were given to them. Anthropometric data were collected using the procedure stipulated by the World Health Organization/United Nations Children’s Fund for taking anthropometric measurements. The height of the mother was measured using an adjustable wooden measuring board, specifically designed to provide accurate measurements (to the nearest 0.1 cm) in developing-country field situations. Similarly, the weight of the mother was measured by using a Seca 876 scale. The weight and height data were used to calculate the BMI, which is defined as weight in kilograms divided by the height in meters squared (kg/m2). A BMI result of 18.5–24.9 was taken as normal, and 17–18.49, 16–16.99, and 16 or less were taken as mild (grade I), moderate (grade II), and severe (grade III) undernutrition, respectively. On the other hand, BMI values of 25–29.9 and ≥30 were defined as overweight and obese, respectively.22,23 Middle upper-arm circumference (MUAC) was measured on the left arm, at the midpoint between the elbow and the shoulder. The arm was relaxed and hanging down the side of the body. MUAC measuring tape was placed around the arm. The value was read from the window of the tape without pinching the arm or leaving the tape loose. An MUAC of less than 23 cm was considered to be a sign of poor nutrition.22–24 Household food-security (access) information was collected by using the questionnaire adopted from the Household Food Insecurity Access Scale, which was developed by the Food and Nutrition Technical Assistance project.25 This instrument consists of nine questions that measure uncertainty on obtaining food, limited access to high-quality foods, and reduction in food quantity in the past 4 weeks. The precoded options were never (0 points), rarely (once or twice in the past 4 weeks; 1 point), sometimes (three to ten times in the past 4 weeks; 2 points), and often (more than ten times in the past 4 weeks; 3 points). Scores for answers to these questions were summed (0–27), and thus a higher value signified a worse condition with more household food insecurity.25 Food diversity was measured by adapting a questionnaire from other standard questionnaires26,27 using the 12 food groups of dietary diversity. The respondents were asked to recall the food items eaten by the household in the previous 7 days. Households who had consumed at least four food groups in the specified period were considered as having diversified food. The questionnaire was pretested in a similar setting after translation into the local language – Amharic. In the process of adapting the questionnaire to the local setting and preparing the 12 food groups, emphasis was given to including each food item consumed in the local population, taking into account the raw materials used to prepare the meal or the dish. The respondents were asked to recall and list all the dishes the household members had eaten during the week. First, the data collectors let the participants describe the dish types and food items consumed in the household in this period, and then the list of the food groups in the questionnaire was explained to be sure that no meal had been forgotten. The 12 food groups and the items included in each group included cereals and cereal products (pasta, macaroni, injera, bread, porridge [kolo, nfro]), meat, offal (goat, camel, beef, chicken/poultry), eggs, roots, tubers (potatoes, sweet potatoes, arrowroot), vegetables (leafy vegetables like cabbage, spinach, Habesha Gomen, tomatoes, carrots, onions), fruit (mango, apple, papaya, banana, orange, strawberry), pulses/legumes, nuts (beans, lentils, peas, guaya), milk and milk products (cheese, yogurt, milk powder), oils/fats (fat, butter, ghee, margarine), sugar and honey, fish and seafood (fried/boiled/roasted), and miscellaneous (including fenugreek, ginger, mace, and pepper). The data collectors were well trained to differentiate easily in which food group the items mentioned by the respondents would be. During training, data collectors became familiar with (and demonstrated understanding well) the meaning of the local terms to differentiate easily and classify in which food groups they could be included. The data collectors and supervisors were university-graduate Bachelor of Science holders. To assure the quality of the data and to make sure all assessment-team members were able to administer the questionnaires properly, 5-day rigorous training of enumerators and supervisors was done. Before actual data collection was undertaken, data collectors and supervisors carried out role-play routines and then pretest field activities. At the end of every data-collection day, each questionnaire was examined for its completeness and consistency by the field supervisors and the principal investigator, and pertinent feedback was given to the data collectors and supervisors. The data were coded, entered, and cleaned with Epi Info version 3.5.3 and exported to SPSS version 20 for further analysis. Descriptive summaries of frequencies, proportions, percentages, mean, standard deviations, and prevalence were determined. To identify predictor variables for maternal nutritional status, a logistic regression model was employed. For determinant-variable identification, first bivariate logistic regression analyses were carried out to identify candidate variables with a P-value <0.25 in the bivariate model, and then all independent variables with P-values <0.25 were entered into the multivariate model.28 At this step, model fitness and the presence of multicollinearity were assessed. The model fitness was checked by observing the difference of the -2 log-likelihood ratio between the model with only the constant and with the predictors. Moreover, Hosmer–Lemeshow goodness-of-fit test was used. The significance of each predictor in the equation was also assessed by Wald statistical test at a significance level of P<0.05. Ethical clearance was obtained from the Institutional Review Board (IRB) of the College of Health Sciences of Addis Ababa University and the Amhara Regional Health Bureau. Participation in the study was on a voluntary basis, and written consent, signed or verified by fingerprint, was obtained from study participants. The consent form was attached with each questionnaire, and before the interview each study participant gave her/his consent. Prior to the questions, the data collectors read the consent form that was available on the front page of the questionnaire, and the respondents mentioned their willingness and the questioning continued on a voluntary basis. The consent form was approved by the IRB and the regional health bureau during ethical approval processes. The IRB approved this research with meeting 050/2013 and protocol 051/12/SPH. Privacy and confidentiality were maintained.

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